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Structural Engineering and Mechanics
  Volume 69, Number 3, February10 2019, pages 317-326

Seismic risk assessment of intake tower in Korea using updated fragility by Bayesian inference
Jahangir Alam, Dookie Kim and Byounghan Choi

    This research aims to assess the tight seismic risk curve of the intake tower at Geumgwang reservoir by considering the recorded historical earthquake data in the Korean Peninsula. The seismic fragility, a significant part of risk assessment, is updated by using Bayesian inference to consider the uncertainties and computational efficiency. The reservoir is one of the largest reservoirs in Korea for the supply of agricultural water. The intake tower controls the release of water from the reservoir. The seismic risk assessment of the intake tower plays an important role in the risk management of the reservoir. Site-specific seismic hazard is computed based on the four different seismic source maps of Korea. Probabilistic Seismic Hazard Analysis (PSHA) method is used to estimate the annual exceedance rate of hazard for corresponding Peak Ground Acceleration (PGA). Hazard deaggregation is shown at two customary hazard levels. Multiple dynamic analyses and a nonlinear static pushover analysis are performed for deriving fragility parameters. Thereafter, Bayesian inference with Markov Chain Monte Carlo (MCMC) is used to update the fragility parameters by integrating the results of the analyses. This study proves to reduce the uncertainties associated with fragility and risk curve, and to increase significant statistical and computational efficiency. The range of seismic risk curve of the intake tower is extracted for the reservoir site by considering four different source models and updated fragility function, which can be effectively used for the risk management and mitigation of reservoir.
Key Words
    seismic risk assessment; intake tower; probabilistic seismic hazard analysis; seismic fragility, bayesian inference
Jahangir Alam and Dookie Kim: Civil and Environmental Engineering, Kunsan National University, 558 Daehak-ro, Gunsan-si 54150, Republic of Korea
Byounghan Choi: Rural Research Institute, 870, Haean-ro Sangnok-gu, Ansan-si Gyeonggi-do, 15634, Republic of Korea

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